scholarly journals Epitope Prediction of Antigen Protein Using Attention-based LSTM Network

2021 ◽  
Vol 29 (0) ◽  
pp. 321-327
Author(s):  
Toshiaki Noumi ◽  
Seiichi Inoue ◽  
Haruka Fujita ◽  
Kugatsu Sadamitsu ◽  
Makoto Sakaguchi ◽  
...  
Keyword(s):  
Epitope Prediction ◽  
Antigen Protein ◽  
Lstm Network

scholarly journals Epitope Prediction of Antigen Protein using Attention-Based LSTM Network

2020 ◽  
Author(s):  
Toshiaki Noumi ◽  
Seiichi Inoue ◽  
Haruka Fujita ◽  
Kugatsu Sadamitsu ◽  
Makoto Sakaguchi ◽  
...  
Keyword(s):  
Short Term Memory ◽  
Epitope Prediction ◽  
Amino Acid Sequences ◽  
Target Sequence ◽  
Epitope Region ◽  
Experimental Prediction ◽  
Specific Antibody Production ◽  
Antigen Protein ◽  
Lstm Network

AbstractB-cells inducing antigen-specific immune responses in vivo produce large amounts of antigen-specific antibodies by recognizing the subregions (epitope regions) of antigen proteins. They can inhibit their functioning by binding antibodies to antigen proteins. Predicting of epitope regions is beneficial for the design and development of vaccines aimed to induce antigen-specific antibody production. However, prediction accuracy requires improvement. The conventional epitope region prediction methods have focused only on the target sequence in the amino acid sequences of an entire antigen protein and have not thoroughly considered its sequence and features as a whole. In the present paper, we propose a deep learning method based on short-term memory with an attention mechanism to consider the characteristics of a whole antigen protein in addition to the target sequence. The proposed method achieves better accuracy compared with the conventional method in the experimental prediction of epitope regions using the data from the immune epitope database.

Multi-Epitope Vaccines (MEVs), as a Novel Strategy Against Infectious Diseases

2020 ◽  
Vol 17 (5) ◽  
pp. 354-364
Author(s):  
Mohammad Mahmoudi Goumari ◽  
Ibrahim Farhani ◽  
Navid Nezafat ◽  
Shirin Mahmoodi
Keyword(s):  
Infectious Diseases ◽  
Epitope Prediction ◽  
Cost Effective ◽  
Antimicrobial Drugs ◽  
Antibiotic Resistant ◽  
Time Consumption ◽  
Preclinical Evaluation ◽  
Structural Evaluation ◽  
Novel Strategy ◽  
Epitope Vaccines

Infectious diseases have caused historical pandemics in the world. Three strategies, including sanitation programs, antimicrobial drugs, and vaccines are considered for the prevention and treatment of infectious diseases. Today, some infectious diseases cause millions of mortalities universally. Due to the emergence of antibiotic-resistant pathogens, as well as some limitations of traditional vaccines, focusing on novel strategies is essential. Multi-Epitope Vaccines (MEVs), as a novel strategy, have been designed based on immunoinformatics methods; epitope prediction by authentic servers, attachment of epitopes using proper linkers, physicochemical, immunological and structural evaluation by bioinformatics tools that are basic stages in MEVs designing. Advantages such as cost-effective, high safety, less time consumption in designing, the application of natural adjuvants, and satisfactory preclinical evaluation outstand MEVs than other types of vaccines. Therefore, MEVs are promising vaccines against resistant diseases such as lower respiratory infection and diarrhea.

Prediction of the Omp16 Epitopes for the Development of an Epitope-based Vaccine Against Brucellosis

2019 ◽  
Vol 19 (1) ◽  
pp. 36-45 ◽  
Author(s):  
Marzieh Rezaei ◽  
Mohammad Rabbani-khorasgani ◽  
Sayyed Hamid Zarkesh-Esfahani ◽  
Rahman Emamzadeh ◽  
Hamid Abtahi
Keyword(s):  
Immune Responses ◽  
B Cell ◽  
Dairy Products ◽  
Bioinformatics Analysis ◽  
Epitope Prediction ◽  
Animal Husbandry ◽  
Zoonotic Diseases ◽  
Recombinant Vaccines ◽  
Protective Capacity ◽  
Tertiary Structures

Background:Brucellosis is an infectious disease caused by Brucella bacteria that cause disease in animals and humans. Brucellosis is one of the most common zoonotic diseases transmitted from animals-to-human through direct contact with infected animals and also consumption of unpasteurized dairy products. Due to the wide incidence of brucellosis in Iran and economical costs in industrial animal husbandry, Vaccination is the best way to prevent this disease. All of the available commercial vaccines against brucellosis are derived from live attenuated strains of Brucella but because of the disadvantage of live attenuated vaccines, protective subunit vaccine against Brucella may be a good candidate for the production of new recombinant vaccines based on Brucella Outer Membrane Protein (OMP) antigens. In the present study, comprehensive bioinformatics analysis has been conducted on prediction software to predict T and B cell epitopes, the secondary and tertiary structures and antigenicity of Omp16 antigen and the validation of used software confirmed by experimental results.Conclusion:The final epitope prediction results have proposed that the three epitopes were predicted for the Omp16 protein with antigenicity ability. We hypothesized that these epitopes likely have the protective capacity to stimulate both the B-cell and T-cell mediated immune responses and so may be effective as an immunogenic candidate for the development of an epitope-based vaccine against brucellosis.

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